A long time ago I tweeted about the need for everyone in the data visualization community to write a book. I wasn’t joking: if you only tweet or write a few posts, you can’t possibly comprehend the lay of your own data visualization land, how deep the rabbit hole goes, the ________________ (choose your own metaphor/cliché).

It doesn’t have to be a formal book, published and all. Call it your data visualization stylebook: something that helps you to unify your thoughts. Then synthesize it into a cheatsheet and append it to every proposal, so that your clients know where you stand and if your views are compatible with theirs. It’s up to you to publish the book: there will always be some overlap with other books, so  you have to decide if the non-overlapping areas bring enough added value to justify publishing it.

To discuss these things I voluntold joined Stephanie Evergreen, Andy Kirk and Alberto Cairo for my first-ever podcast in English (I write and read in English all the time, but I don’t often actually speak it – I’m working on that now, but I do prefer to write, even in my mother tongue, Portuguese. You can hear the recording here:

And here are the Amazon links, in case you want to help us becoming filthy rich authors:

This is a clear example of how four data visualization books do overlap in some areas but complement each other rather nicely, from a broader perspective (Andy’s) to a more hand-on (Stephanie’s), mine between the two, and Alberto’s as an outlier 🙂

One of the things I learned along the process is how the work behind the book by the author him/herself, but also editor’s work, is so invisible and under-appreciated, just like data cleansing in data visualization. But now I know why people write a second book: they become addicted to discovery and creation, and probably to the emotional roller-coaster, too.

Imagy by cs:User:ŠJů (Čeština: vlastní fotografieEnglish: own work) [GFDL, CC-BY-SA-3.0 or CC BY-SA 2.5-2.0-1.0], via Wikimedia Commons